Dataset statistics
| Dataset A | Dataset B | |
|---|---|---|
| Number of variables | 12 | 12 |
| Number of observations | 446 | 446 |
| Missing cells | 447 | 436 |
| Missing cells (%) | 8.4% | 8.1% |
| Duplicate rows | 0 | 0 |
| Duplicate rows (%) | 0.0% | 0.0% |
| Total size in memory | 45.3 KiB | 45.3 KiB |
| Average record size in memory | 104.0 B | 104.0 B |
Variable types
| Dataset A | Dataset B | |
|---|---|---|
| Numeric | 5 | 5 |
| Categorical | 4 | 4 |
| Text | 3 | 3 |
| Dataset A | Dataset B | |
|---|---|---|
Age has 95 (21.3%) missing values | Age has 86 (19.3%) missing values | Missing |
Cabin has 350 (78.5%) missing values | Cabin has 349 (78.3%) missing values | Missing |
PassengerId has unique values | PassengerId has unique values | Unique |
Name has unique values | Name has unique values | Unique |
SibSp has 306 (68.6%) zeros | SibSp has 307 (68.8%) zeros | Zeros |
Parch has 340 (76.2%) zeros | Parch has 341 (76.5%) zeros | Zeros |
Fare has 6 (1.3%) zeros | Fare has 7 (1.6%) zeros | Zeros |
Reproduction
| Dataset A | Dataset B | |
|---|---|---|
| Analysis started | 2024-05-07 00:00:52.171376 | 2024-05-07 00:00:56.179014 |
| Analysis finished | 2024-05-07 00:00:56.177861 | 2024-05-07 00:00:59.194845 |
| Duration | 4.01 seconds | 3.02 seconds |
| Software version | ydata-profiling v0.0.dev0 | ydata-profiling v0.0.dev0 |
| Download configuration | config.json | config.json |
PassengerId
Real number (ℝ)
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 446 | 446 |
| Distinct (%) | 100.0% | 100.0% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Infinite | 0 | 0 |
| Infinite (%) | 0.0% | 0.0% |
| Mean | 447.45516 | 452.88789 |
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 1 | 2 |
| Maximum | 891 | 891 |
| Zeros | 0 | 0 |
| Zeros (%) | 0.0% | 0.0% |
| Negative | 0 | 0 |
| Negative (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
Quantile statistics
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 1 | 2 |
| 5-th percentile | 41.25 | 53.25 |
| Q1 | 230.5 | 233.5 |
| median | 450.5 | 470 |
| Q3 | 670.5 | 664.75 |
| 95-th percentile | 843.75 | 851.5 |
| Maximum | 891 | 891 |
| Range | 890 | 889 |
| Interquartile range (IQR) | 440 | 431.25 |
Descriptive statistics
| Dataset A | Dataset B | |
|---|---|---|
| Standard deviation | 258.2702 | 254.17386 |
| Coefficient of variation (CV) | 0.57719796 | 0.56122909 |
| Kurtosis | -1.1844795 | -1.1466849 |
| Mean | 447.45516 | 452.88789 |
| Median Absolute Deviation (MAD) | 220.5 | 215.5 |
| Skewness | -0.019543894 | -0.032871666 |
| Sum | 199565 | 201988 |
| Variance | 66703.498 | 64604.351 |
| Monotonicity | Not monotonic | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 191 | 1 | 0.2% |
| 731 | 1 | 0.2% |
| 188 | 1 | 0.2% |
| 299 | 1 | 0.2% |
| 606 | 1 | 0.2% |
| 248 | 1 | 0.2% |
| 796 | 1 | 0.2% |
| 86 | 1 | 0.2% |
| 420 | 1 | 0.2% |
| 548 | 1 | 0.2% |
| Other values (436) | 436 |
| Value | Count | Frequency (%) |
| 694 | 1 | 0.2% |
| 261 | 1 | 0.2% |
| 798 | 1 | 0.2% |
| 444 | 1 | 0.2% |
| 69 | 1 | 0.2% |
| 883 | 1 | 0.2% |
| 374 | 1 | 0.2% |
| 24 | 1 | 0.2% |
| 155 | 1 | 0.2% |
| 591 | 1 | 0.2% |
| Other values (436) | 436 |
| Value | Count | Frequency (%) |
| 1 | 1 | |
| 3 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 1 | |
| 12 | 1 | |
| 15 | 1 | |
| 16 | 1 |
| Value | Count | Frequency (%) |
| 2 | 1 | |
| 3 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 11 | 1 | |
| 15 | 1 | |
| 16 | 1 | |
| 21 | 1 | |
| 23 | 1 | |
| 24 | 1 |
| Value | Count | Frequency (%) |
| 2 | 1 | |
| 3 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 11 | 1 | |
| 15 | 1 | |
| 16 | 1 | |
| 21 | 1 | |
| 23 | 1 | |
| 24 | 1 |
| Value | Count | Frequency (%) |
| 1 | 1 | |
| 3 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 1 | |
| 12 | 1 | |
| 15 | 1 | |
| 16 | 1 |
Survived
Categorical
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 2 | 2 |
| Distinct (%) | 0.4% | 0.4% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
| 0 | |
|---|---|
| 1 |
| 0 | |
|---|---|
| 1 |
Length
| Dataset A | Dataset B | |
|---|---|---|
| Max length | 1 | 1 |
| Median length | 1 | 1 |
| Mean length | 1 | 1 |
| Min length | 1 | 1 |
Characters and Unicode
| Dataset A | Dataset B | |
|---|---|---|
| Total characters | 446 | 446 |
| Distinct characters | 2 | 2 |
| Distinct categories | 1 | 1 ? |
| Distinct scripts | 1 | 1 ? |
| Distinct blocks | 1 | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Dataset A | Dataset B | |
|---|---|---|
| Unique | 0 | 0 ? |
| Unique (%) | 0.0% | 0.0% |
Sample
| Dataset A | Dataset B | |
|---|---|---|
| 1st row | 1 | 0 |
| 2nd row | 1 | 1 |
| 3rd row | 1 | 0 |
| 4th row | 1 | 1 |
| 5th row | 0 | 0 |
Common Values
| Value | Count | Frequency (%) |
| 0 | 282 | |
| 1 | 164 |
| Value | Count | Frequency (%) |
| 0 | 274 | |
| 1 | 172 |
Length
Histogram of lengths of the category
Common Values (Plot)
Dataset A
Dataset B
| Value | Count | Frequency (%) |
| 0 | 282 | |
| 1 | 164 |
| Value | Count | Frequency (%) |
| 0 | 274 | |
| 1 | 172 |
Most occurring characters
| Value | Count | Frequency (%) |
| 0 | 282 | |
| 1 | 164 |
| Value | Count | Frequency (%) |
| 0 | 274 | |
| 1 | 172 |
Most occurring categories
| Value | Count | Frequency (%) |
| (unknown) | 446 |
| Value | Count | Frequency (%) |
| (unknown) | 446 |
Most frequent character per category
(unknown)
| Value | Count | Frequency (%) |
| 0 | 282 | |
| 1 | 164 |
| Value | Count | Frequency (%) |
| 0 | 274 | |
| 1 | 172 |
Most occurring scripts
| Value | Count | Frequency (%) |
| (unknown) | 446 |
| Value | Count | Frequency (%) |
| (unknown) | 446 |
Most frequent character per script
(unknown)
| Value | Count | Frequency (%) |
| 0 | 282 | |
| 1 | 164 |
| Value | Count | Frequency (%) |
| 0 | 274 | |
| 1 | 172 |
Most occurring blocks
| Value | Count | Frequency (%) |
| (unknown) | 446 |
| Value | Count | Frequency (%) |
| (unknown) | 446 |
Most frequent character per block
(unknown)
| Value | Count | Frequency (%) |
| 0 | 282 | |
| 1 | 164 |
| Value | Count | Frequency (%) |
| 0 | 274 | |
| 1 | 172 |
Pclass
Categorical
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 3 | 3 |
| Distinct (%) | 0.7% | 0.7% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
| 3 | |
|---|---|
| 1 | |
| 2 |
| 3 | |
|---|---|
| 1 | |
| 2 |
Length
| Dataset A | Dataset B | |
|---|---|---|
| Max length | 1 | 1 |
| Median length | 1 | 1 |
| Mean length | 1 | 1 |
| Min length | 1 | 1 |
Characters and Unicode
| Dataset A | Dataset B | |
|---|---|---|
| Total characters | 446 | 446 |
| Distinct characters | 3 | 3 |
| Distinct categories | 1 | 1 ? |
| Distinct scripts | 1 | 1 ? |
| Distinct blocks | 1 | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Dataset A | Dataset B | |
|---|---|---|
| Unique | 0 | 0 ? |
| Unique (%) | 0.0% | 0.0% |
Sample
| Dataset A | Dataset B | |
|---|---|---|
| 1st row | 2 | 3 |
| 2nd row | 2 | 1 |
| 3rd row | 1 | 1 |
| 4th row | 1 | 3 |
| 5th row | 3 | 3 |
Common Values
| Value | Count | Frequency (%) |
| 3 | 245 | |
| 1 | 106 | |
| 2 | 95 | 21.3% |
| Value | Count | Frequency (%) |
| 3 | 245 | |
| 1 | 107 | |
| 2 | 94 | 21.1% |
Length
Histogram of lengths of the category
Common Values (Plot)
Dataset A
Dataset B
| Value | Count | Frequency (%) |
| 3 | 245 | |
| 1 | 106 | |
| 2 | 95 | 21.3% |
| Value | Count | Frequency (%) |
| 3 | 245 | |
| 1 | 107 | |
| 2 | 94 | 21.1% |
Most occurring characters
| Value | Count | Frequency (%) |
| 3 | 245 | |
| 1 | 106 | |
| 2 | 95 | 21.3% |
| Value | Count | Frequency (%) |
| 3 | 245 | |
| 1 | 107 | |
| 2 | 94 | 21.1% |
Most occurring categories
| Value | Count | Frequency (%) |
| (unknown) | 446 |
| Value | Count | Frequency (%) |
| (unknown) | 446 |
Most frequent character per category
(unknown)
| Value | Count | Frequency (%) |
| 3 | 245 | |
| 1 | 106 | |
| 2 | 95 | 21.3% |
| Value | Count | Frequency (%) |
| 3 | 245 | |
| 1 | 107 | |
| 2 | 94 | 21.1% |
Most occurring scripts
| Value | Count | Frequency (%) |
| (unknown) | 446 |
| Value | Count | Frequency (%) |
| (unknown) | 446 |
Most frequent character per script
(unknown)
| Value | Count | Frequency (%) |
| 3 | 245 | |
| 1 | 106 | |
| 2 | 95 | 21.3% |
| Value | Count | Frequency (%) |
| 3 | 245 | |
| 1 | 107 | |
| 2 | 94 | 21.1% |
Most occurring blocks
| Value | Count | Frequency (%) |
| (unknown) | 446 |
| Value | Count | Frequency (%) |
| (unknown) | 446 |
Most frequent character per block
(unknown)
| Value | Count | Frequency (%) |
| 3 | 245 | |
| 1 | 106 | |
| 2 | 95 | 21.3% |
| Value | Count | Frequency (%) |
| 3 | 245 | |
| 1 | 107 | |
| 2 | 94 | 21.1% |
Name
['Text', 'Text']
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 446 | 446 |
| Distinct (%) | 100.0% | 100.0% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
Length
| Dataset A | Dataset B | |
|---|---|---|
| Max length | 67 | 67 |
| Median length | 52 | 49 |
| Mean length | 26.883408 | 26.70852 |
| Min length | 12 | 12 |
Characters and Unicode
| Dataset A | Dataset B | |
|---|---|---|
| Total characters | 11990 | 11912 |
| Distinct characters | 58 | 59 |
| Distinct categories | 1 | 1 ? |
| Distinct scripts | 1 | 1 ? |
| Distinct blocks | 1 | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Dataset A | Dataset B | |
|---|---|---|
| Unique | 446 | 446 ? |
| Unique (%) | 100.0% | 100.0% |
Sample
| Dataset A | Dataset B | |
|---|---|---|
| 1st row | Pinsky, Mrs. (Rosa) | Saad, Mr. Khalil |
| 2nd row | Sinkkonen, Miss. Anna | Carter, Mrs. William Ernest (Lucile Polk) |
| 3rd row | Newsom, Miss. Helen Monypeny | Allison, Miss. Helen Loraine |
| 4th row | Shutes, Miss. Elizabeth W | Barah, Mr. Hanna Assi |
| 5th row | Cor, Mr. Liudevit | Karaic, Mr. Milan |
| Value | Count | Frequency (%) |
| mr | 261 | 14.4% |
| miss | 89 | 4.9% |
| mrs | 66 | 3.6% |
| john | 27 | 1.5% |
| william | 24 | 1.3% |
| master | 20 | 1.1% |
| henry | 16 | 0.9% |
| james | 14 | 0.8% |
| charles | 14 | 0.8% |
| anna | 13 | 0.7% |
| Other values (888) | 1269 |
| Value | Count | Frequency (%) |
| mr | 260 | 14.4% |
| miss | 93 | 5.2% |
| mrs | 65 | 3.6% |
| william | 25 | 1.4% |
| henry | 21 | 1.2% |
| john | 19 | 1.1% |
| master | 15 | 0.8% |
| james | 12 | 0.7% |
| mary | 12 | 0.7% |
| frederick | 11 | 0.6% |
| Other values (902) | 1267 |
Most occurring characters
| Value | Count | Frequency (%) |
| 1369 | 11.4% | |
| r | 972 | 8.1% |
| e | 840 | 7.0% |
| a | 835 | 7.0% |
| n | 689 | 5.7% |
| i | 642 | 5.4% |
| s | 635 | 5.3% |
| M | 570 | 4.8% |
| l | 522 | 4.4% |
| o | 510 | 4.3% |
| Other values (48) | 4406 |
| Value | Count | Frequency (%) |
| 1356 | 11.4% | |
| r | 982 | 8.2% |
| a | 831 | 7.0% |
| e | 829 | 7.0% |
| i | 679 | 5.7% |
| n | 670 | 5.6% |
| s | 631 | 5.3% |
| M | 556 | 4.7% |
| l | 509 | 4.3% |
| o | 475 | 4.0% |
| Other values (49) | 4394 |
Most occurring categories
| Value | Count | Frequency (%) |
| (unknown) | 11990 |
| Value | Count | Frequency (%) |
| (unknown) | 11912 |
Most frequent character per category
(unknown)
| Value | Count | Frequency (%) |
| 1369 | 11.4% | |
| r | 972 | 8.1% |
| e | 840 | 7.0% |
| a | 835 | 7.0% |
| n | 689 | 5.7% |
| i | 642 | 5.4% |
| s | 635 | 5.3% |
| M | 570 | 4.8% |
| l | 522 | 4.4% |
| o | 510 | 4.3% |
| Other values (48) | 4406 |
| Value | Count | Frequency (%) |
| 1356 | 11.4% | |
| r | 982 | 8.2% |
| a | 831 | 7.0% |
| e | 829 | 7.0% |
| i | 679 | 5.7% |
| n | 670 | 5.6% |
| s | 631 | 5.3% |
| M | 556 | 4.7% |
| l | 509 | 4.3% |
| o | 475 | 4.0% |
| Other values (49) | 4394 |
Most occurring scripts
| Value | Count | Frequency (%) |
| (unknown) | 11990 |
| Value | Count | Frequency (%) |
| (unknown) | 11912 |
Most frequent character per script
(unknown)
| Value | Count | Frequency (%) |
| 1369 | 11.4% | |
| r | 972 | 8.1% |
| e | 840 | 7.0% |
| a | 835 | 7.0% |
| n | 689 | 5.7% |
| i | 642 | 5.4% |
| s | 635 | 5.3% |
| M | 570 | 4.8% |
| l | 522 | 4.4% |
| o | 510 | 4.3% |
| Other values (48) | 4406 |
| Value | Count | Frequency (%) |
| 1356 | 11.4% | |
| r | 982 | 8.2% |
| a | 831 | 7.0% |
| e | 829 | 7.0% |
| i | 679 | 5.7% |
| n | 670 | 5.6% |
| s | 631 | 5.3% |
| M | 556 | 4.7% |
| l | 509 | 4.3% |
| o | 475 | 4.0% |
| Other values (49) | 4394 |
Most occurring blocks
| Value | Count | Frequency (%) |
| (unknown) | 11990 |
| Value | Count | Frequency (%) |
| (unknown) | 11912 |
Most frequent character per block
(unknown)
| Value | Count | Frequency (%) |
| 1369 | 11.4% | |
| r | 972 | 8.1% |
| e | 840 | 7.0% |
| a | 835 | 7.0% |
| n | 689 | 5.7% |
| i | 642 | 5.4% |
| s | 635 | 5.3% |
| M | 570 | 4.8% |
| l | 522 | 4.4% |
| o | 510 | 4.3% |
| Other values (48) | 4406 |
| Value | Count | Frequency (%) |
| 1356 | 11.4% | |
| r | 982 | 8.2% |
| a | 831 | 7.0% |
| e | 829 | 7.0% |
| i | 679 | 5.7% |
| n | 670 | 5.6% |
| s | 631 | 5.3% |
| M | 556 | 4.7% |
| l | 509 | 4.3% |
| o | 475 | 4.0% |
| Other values (49) | 4394 |
Sex
Categorical
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 2 | 2 |
| Distinct (%) | 0.4% | 0.4% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
| male | |
|---|---|
| female |
| male | |
|---|---|
| female |
Length
| Dataset A | Dataset B | |
|---|---|---|
| Max length | 6 | 6 |
| Median length | 4 | 4 |
| Mean length | 4.7040359 | 4.7174888 |
| Min length | 4 | 4 |
Characters and Unicode
| Dataset A | Dataset B | |
|---|---|---|
| Total characters | 2098 | 2104 |
| Distinct characters | 5 | 5 |
| Distinct categories | 1 | 1 ? |
| Distinct scripts | 1 | 1 ? |
| Distinct blocks | 1 | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Dataset A | Dataset B | |
|---|---|---|
| Unique | 0 | 0 ? |
| Unique (%) | 0.0% | 0.0% |
Sample
| Dataset A | Dataset B | |
|---|---|---|
| 1st row | female | male |
| 2nd row | female | female |
| 3rd row | female | female |
| 4th row | female | male |
| 5th row | male | male |
Common Values
| Value | Count | Frequency (%) |
| male | 289 | |
| female | 157 |
| Value | Count | Frequency (%) |
| male | 286 | |
| female | 160 |
Length
Histogram of lengths of the category
Common Values (Plot)
Dataset A
Dataset B
| Value | Count | Frequency (%) |
| male | 289 | |
| female | 157 |
| Value | Count | Frequency (%) |
| male | 286 | |
| female | 160 |
Most occurring characters
| Value | Count | Frequency (%) |
| e | 603 | |
| m | 446 | |
| a | 446 | |
| l | 446 | |
| f | 157 | 7.5% |
| Value | Count | Frequency (%) |
| e | 606 | |
| m | 446 | |
| a | 446 | |
| l | 446 | |
| f | 160 | 7.6% |
Most occurring categories
| Value | Count | Frequency (%) |
| (unknown) | 2098 |
| Value | Count | Frequency (%) |
| (unknown) | 2104 |
Most frequent character per category
(unknown)
| Value | Count | Frequency (%) |
| e | 603 | |
| m | 446 | |
| a | 446 | |
| l | 446 | |
| f | 157 | 7.5% |
| Value | Count | Frequency (%) |
| e | 606 | |
| m | 446 | |
| a | 446 | |
| l | 446 | |
| f | 160 | 7.6% |
Most occurring scripts
| Value | Count | Frequency (%) |
| (unknown) | 2098 |
| Value | Count | Frequency (%) |
| (unknown) | 2104 |
Most frequent character per script
(unknown)
| Value | Count | Frequency (%) |
| e | 603 | |
| m | 446 | |
| a | 446 | |
| l | 446 | |
| f | 157 | 7.5% |
| Value | Count | Frequency (%) |
| e | 606 | |
| m | 446 | |
| a | 446 | |
| l | 446 | |
| f | 160 | 7.6% |
Most occurring blocks
| Value | Count | Frequency (%) |
| (unknown) | 2098 |
| Value | Count | Frequency (%) |
| (unknown) | 2104 |
Most frequent character per block
(unknown)
| Value | Count | Frequency (%) |
| e | 603 | |
| m | 446 | |
| a | 446 | |
| l | 446 | |
| f | 157 | 7.5% |
| Value | Count | Frequency (%) |
| e | 606 | |
| m | 446 | |
| a | 446 | |
| l | 446 | |
| f | 160 | 7.6% |
Age
Real number (ℝ)
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 77 | 71 |
| Distinct (%) | 21.9% | 19.7% |
| Missing | 95 | 86 |
| Missing (%) | 21.3% | 19.3% |
| Infinite | 0 | 0 |
| Infinite (%) | 0.0% | 0.0% |
| Mean | 30.184245 | 30.20025 |
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 0.75 | 0.42 |
| Maximum | 71 | 74 |
| Zeros | 0 | 0 |
| Zeros (%) | 0.0% | 0.0% |
| Negative | 0 | 0 |
| Negative (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
Quantile statistics
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 0.75 | 0.42 |
| 5-th percentile | 8 | 5.95 |
| Q1 | 21 | 21 |
| median | 29 | 29 |
| Q3 | 38 | 38.25 |
| 95-th percentile | 56 | 55.525 |
| Maximum | 71 | 74 |
| Range | 70.25 | 73.58 |
| Interquartile range (IQR) | 17 | 17.25 |
Descriptive statistics
| Dataset A | Dataset B | |
|---|---|---|
| Standard deviation | 13.761 | 14.318968 |
| Coefficient of variation (CV) | 0.45590009 | 0.47413408 |
| Kurtosis | 0.062787111 | 0.2474339 |
| Mean | 30.184245 | 30.20025 |
| Median Absolute Deviation (MAD) | 8 | 8 |
| Skewness | 0.33499726 | 0.42833798 |
| Sum | 10594.67 | 10872.09 |
| Variance | 189.36513 | 205.03284 |
| Monotonicity | Not monotonic | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 22 | 20 | 4.5% |
| 30 | 16 | 3.6% |
| 29 | 14 | 3.1% |
| 24 | 13 | 2.9% |
| 18 | 13 | 2.9% |
| 31 | 12 | 2.7% |
| 27 | 12 | 2.7% |
| 36 | 12 | 2.7% |
| 25 | 11 | 2.5% |
| 19 | 11 | 2.5% |
| Other values (67) | 217 | |
| (Missing) | 95 |
| Value | Count | Frequency (%) |
| 22 | 18 | 4.0% |
| 24 | 17 | 3.8% |
| 21 | 15 | 3.4% |
| 32 | 14 | 3.1% |
| 18 | 13 | 2.9% |
| 28 | 12 | 2.7% |
| 35 | 12 | 2.7% |
| 30 | 12 | 2.7% |
| 36 | 11 | 2.5% |
| 26 | 11 | 2.5% |
| Other values (61) | 225 | |
| (Missing) | 86 | 19.3% |
| Value | Count | Frequency (%) |
| 0.75 | 1 | 0.2% |
| 0.92 | 1 | 0.2% |
| 1 | 3 | |
| 2 | 5 | |
| 3 | 2 | 0.4% |
| 4 | 3 | |
| 5 | 1 | 0.2% |
| 7 | 1 | 0.2% |
| 8 | 3 | |
| 9 | 1 | 0.2% |
| Value | Count | Frequency (%) |
| 0.42 | 1 | 0.2% |
| 0.67 | 1 | 0.2% |
| 1 | 3 | |
| 2 | 5 | |
| 3 | 2 | 0.4% |
| 4 | 4 | |
| 5 | 2 | 0.4% |
| 6 | 2 | 0.4% |
| 7 | 2 | 0.4% |
| 8 | 2 | 0.4% |
| Value | Count | Frequency (%) |
| 0.42 | 1 | 0.2% |
| 0.67 | 1 | 0.2% |
| 1 | 3 | |
| 2 | 5 | |
| 3 | 2 | 0.4% |
| 4 | 4 | |
| 5 | 2 | 0.4% |
| 6 | 2 | 0.4% |
| 7 | 2 | 0.4% |
| 8 | 2 | 0.4% |
| Value | Count | Frequency (%) |
| 0.75 | 1 | 0.2% |
| 0.92 | 1 | 0.2% |
| 1 | 3 | |
| 2 | 5 | |
| 3 | 2 | 0.4% |
| 4 | 3 | |
| 5 | 1 | 0.2% |
| 7 | 1 | 0.2% |
| 8 | 3 | |
| 9 | 1 | 0.2% |
SibSp
Real number (ℝ)
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 7 | 7 |
| Distinct (%) | 1.6% | 1.6% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Infinite | 0 | 0 |
| Infinite (%) | 0.0% | 0.0% |
| Mean | 0.51345291 | 0.5 |
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 0 | 0 |
| Maximum | 8 | 8 |
| Zeros | 306 | 307 |
| Zeros (%) | 68.6% | 68.8% |
| Negative | 0 | 0 |
| Negative (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
Quantile statistics
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 0 | 0 |
| 5-th percentile | 0 | 0 |
| Q1 | 0 | 0 |
| median | 0 | 0 |
| Q3 | 1 | 1 |
| 95-th percentile | 3 | 2 |
| Maximum | 8 | 8 |
| Range | 8 | 8 |
| Interquartile range (IQR) | 1 | 1 |
Descriptive statistics
| Dataset A | Dataset B | |
|---|---|---|
| Standard deviation | 1.0866082 | 1.0679183 |
| Coefficient of variation (CV) | 2.1162763 | 2.1358365 |
| Kurtosis | 17.276864 | 18.684215 |
| Mean | 0.51345291 | 0.5 |
| Median Absolute Deviation (MAD) | 0 | 0 |
| Skewness | 3.6337471 | 3.7698908 |
| Sum | 229 | 223 |
| Variance | 1.1807175 | 1.1404494 |
| Monotonicity | Not monotonic | Not monotonic |
Histogram with fixed size bins (bins=7)
| Value | Count | Frequency (%) |
| 0 | 306 | |
| 1 | 106 | 23.8% |
| 3 | 10 | 2.2% |
| 2 | 9 | 2.0% |
| 4 | 9 | 2.0% |
| 5 | 3 | 0.7% |
| 8 | 3 | 0.7% |
| Value | Count | Frequency (%) |
| 0 | 307 | |
| 1 | 106 | 23.8% |
| 2 | 12 | 2.7% |
| 4 | 9 | 2.0% |
| 3 | 6 | 1.3% |
| 5 | 3 | 0.7% |
| 8 | 3 | 0.7% |
| Value | Count | Frequency (%) |
| 0 | 306 | |
| 1 | 106 | 23.8% |
| 2 | 9 | 2.0% |
| 3 | 10 | 2.2% |
| 4 | 9 | 2.0% |
| 5 | 3 | 0.7% |
| 8 | 3 | 0.7% |
| Value | Count | Frequency (%) |
| 0 | 307 | |
| 1 | 106 | 23.8% |
| 2 | 12 | 2.7% |
| 3 | 6 | 1.3% |
| 4 | 9 | 2.0% |
| 5 | 3 | 0.7% |
| 8 | 3 | 0.7% |
| Value | Count | Frequency (%) |
| 0 | 307 | |
| 1 | 106 | 23.8% |
| 2 | 12 | 2.7% |
| 3 | 6 | 1.3% |
| 4 | 9 | 2.0% |
| 5 | 3 | 0.7% |
| 8 | 3 | 0.7% |
| Value | Count | Frequency (%) |
| 0 | 306 | |
| 1 | 106 | 23.8% |
| 2 | 9 | 2.0% |
| 3 | 10 | 2.2% |
| 4 | 9 | 2.0% |
| 5 | 3 | 0.7% |
| 8 | 3 | 0.7% |
Parch
Real number (ℝ)
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 6 | 7 |
| Distinct (%) | 1.3% | 1.6% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Infinite | 0 | 0 |
| Infinite (%) | 0.0% | 0.0% |
| Mean | 0.39013453 | 0.38116592 |
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 0 | 0 |
| Maximum | 5 | 6 |
| Zeros | 340 | 341 |
| Zeros (%) | 76.2% | 76.5% |
| Negative | 0 | 0 |
| Negative (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
Quantile statistics
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 0 | 0 |
| 5-th percentile | 0 | 0 |
| Q1 | 0 | 0 |
| median | 0 | 0 |
| Q3 | 0 | 0 |
| 95-th percentile | 2 | 2 |
| Maximum | 5 | 6 |
| Range | 5 | 6 |
| Interquartile range (IQR) | 0 | 0 |
Descriptive statistics
| Dataset A | Dataset B | |
|---|---|---|
| Standard deviation | 0.84283709 | 0.81447825 |
| Coefficient of variation (CV) | 2.1603755 | 2.1368076 |
| Kurtosis | 9.632618 | 10.684819 |
| Mean | 0.39013453 | 0.38116592 |
| Median Absolute Deviation (MAD) | 0 | 0 |
| Skewness | 2.8258645 | 2.8314936 |
| Sum | 174 | 170 |
| Variance | 0.71037436 | 0.66337482 |
| Monotonicity | Not monotonic | Not monotonic |
Histogram with fixed size bins (bins=6)
| Value | Count | Frequency (%) |
| 0 | 340 | |
| 1 | 59 | 13.2% |
| 2 | 38 | 8.5% |
| 4 | 4 | 0.9% |
| 5 | 4 | 0.9% |
| 3 | 1 | 0.2% |
| Value | Count | Frequency (%) |
| 0 | 341 | |
| 1 | 56 | 12.6% |
| 2 | 42 | 9.4% |
| 5 | 2 | 0.4% |
| 4 | 2 | 0.4% |
| 3 | 2 | 0.4% |
| 6 | 1 | 0.2% |
| Value | Count | Frequency (%) |
| 0 | 340 | |
| 1 | 59 | 13.2% |
| 2 | 38 | 8.5% |
| 3 | 1 | 0.2% |
| 4 | 4 | 0.9% |
| 5 | 4 | 0.9% |
| Value | Count | Frequency (%) |
| 0 | 341 | |
| 1 | 56 | 12.6% |
| 2 | 42 | 9.4% |
| 3 | 2 | 0.4% |
| 4 | 2 | 0.4% |
| 5 | 2 | 0.4% |
| 6 | 1 | 0.2% |
| Value | Count | Frequency (%) |
| 0 | 341 | |
| 1 | 56 | 12.6% |
| 2 | 42 | 9.4% |
| 3 | 2 | 0.4% |
| 4 | 2 | 0.4% |
| 5 | 2 | 0.4% |
| 6 | 1 | 0.2% |
| Value | Count | Frequency (%) |
| 0 | 340 | |
| 1 | 59 | 13.2% |
| 2 | 38 | 8.5% |
| 3 | 1 | 0.2% |
| 4 | 4 | 0.9% |
| 5 | 4 | 0.9% |
Ticket
['Text', 'Text']
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 382 | 384 |
| Distinct (%) | 85.7% | 86.1% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
Length
| Dataset A | Dataset B | |
|---|---|---|
| Max length | 18 | 18 |
| Median length | 17 | 17 |
| Mean length | 6.8766816 | 6.9349776 |
| Min length | 4 | 3 |
Characters and Unicode
| Dataset A | Dataset B | |
|---|---|---|
| Total characters | 3067 | 3093 |
| Distinct characters | 32 | 35 |
| Distinct categories | 1 | 1 ? |
| Distinct scripts | 1 | 1 ? |
| Distinct blocks | 1 | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Dataset A | Dataset B | |
|---|---|---|
| Unique | 334 | 336 ? |
| Unique (%) | 74.9% | 75.3% |
Sample
| Dataset A | Dataset B | |
|---|---|---|
| 1st row | 234604 | 2672 |
| 2nd row | 250648 | 113760 |
| 3rd row | 11752 | 113781 |
| 4th row | PC 17582 | 2663 |
| 5th row | 349231 | 349246 |
| Value | Count | Frequency (%) |
| pc | 30 | 5.3% |
| c.a | 14 | 2.5% |
| a/5 | 9 | 1.6% |
| ston/o | 7 | 1.2% |
| 2 | 7 | 1.2% |
| w./c | 6 | 1.1% |
| ca | 6 | 1.1% |
| sc/paris | 6 | 1.1% |
| soton/o.q | 5 | 0.9% |
| soton/oq | 5 | 0.9% |
| Other values (401) | 476 |
| Value | Count | Frequency (%) |
| pc | 30 | 5.2% |
| c.a | 16 | 2.8% |
| ston/o | 9 | 1.6% |
| 2 | 9 | 1.6% |
| ca | 8 | 1.4% |
| a/5 | 8 | 1.4% |
| w./c | 7 | 1.2% |
| soton/oq | 6 | 1.0% |
| soton/o.q | 5 | 0.9% |
| 2144 | 4 | 0.7% |
| Other values (402) | 476 |
Most occurring characters
| Value | Count | Frequency (%) |
| 3 | 374 | |
| 1 | 366 | |
| 2 | 300 | |
| 7 | 236 | 7.7% |
| 4 | 221 | 7.2% |
| 0 | 211 | 6.9% |
| 6 | 196 | 6.4% |
| 5 | 188 | 6.1% |
| 9 | 172 | 5.6% |
| 8 | 150 | 4.9% |
| Other values (22) | 653 |
| Value | Count | Frequency (%) |
| 3 | 381 | |
| 1 | 353 | |
| 2 | 295 | |
| 4 | 236 | 7.6% |
| 7 | 233 | 7.5% |
| 0 | 217 | 7.0% |
| 6 | 212 | 6.9% |
| 5 | 187 | 6.0% |
| 9 | 169 | 5.5% |
| 8 | 151 | 4.9% |
| Other values (25) | 659 |
Most occurring categories
| Value | Count | Frequency (%) |
| (unknown) | 3067 |
| Value | Count | Frequency (%) |
| (unknown) | 3093 |
Most frequent character per category
(unknown)
| Value | Count | Frequency (%) |
| 3 | 374 | |
| 1 | 366 | |
| 2 | 300 | |
| 7 | 236 | 7.7% |
| 4 | 221 | 7.2% |
| 0 | 211 | 6.9% |
| 6 | 196 | 6.4% |
| 5 | 188 | 6.1% |
| 9 | 172 | 5.6% |
| 8 | 150 | 4.9% |
| Other values (22) | 653 |
| Value | Count | Frequency (%) |
| 3 | 381 | |
| 1 | 353 | |
| 2 | 295 | |
| 4 | 236 | 7.6% |
| 7 | 233 | 7.5% |
| 0 | 217 | 7.0% |
| 6 | 212 | 6.9% |
| 5 | 187 | 6.0% |
| 9 | 169 | 5.5% |
| 8 | 151 | 4.9% |
| Other values (25) | 659 |
Most occurring scripts
| Value | Count | Frequency (%) |
| (unknown) | 3067 |
| Value | Count | Frequency (%) |
| (unknown) | 3093 |
Most frequent character per script
(unknown)
| Value | Count | Frequency (%) |
| 3 | 374 | |
| 1 | 366 | |
| 2 | 300 | |
| 7 | 236 | 7.7% |
| 4 | 221 | 7.2% |
| 0 | 211 | 6.9% |
| 6 | 196 | 6.4% |
| 5 | 188 | 6.1% |
| 9 | 172 | 5.6% |
| 8 | 150 | 4.9% |
| Other values (22) | 653 |
| Value | Count | Frequency (%) |
| 3 | 381 | |
| 1 | 353 | |
| 2 | 295 | |
| 4 | 236 | 7.6% |
| 7 | 233 | 7.5% |
| 0 | 217 | 7.0% |
| 6 | 212 | 6.9% |
| 5 | 187 | 6.0% |
| 9 | 169 | 5.5% |
| 8 | 151 | 4.9% |
| Other values (25) | 659 |
Most occurring blocks
| Value | Count | Frequency (%) |
| (unknown) | 3067 |
| Value | Count | Frequency (%) |
| (unknown) | 3093 |
Most frequent character per block
(unknown)
| Value | Count | Frequency (%) |
| 3 | 374 | |
| 1 | 366 | |
| 2 | 300 | |
| 7 | 236 | 7.7% |
| 4 | 221 | 7.2% |
| 0 | 211 | 6.9% |
| 6 | 196 | 6.4% |
| 5 | 188 | 6.1% |
| 9 | 172 | 5.6% |
| 8 | 150 | 4.9% |
| Other values (22) | 653 |
| Value | Count | Frequency (%) |
| 3 | 381 | |
| 1 | 353 | |
| 2 | 295 | |
| 4 | 236 | 7.6% |
| 7 | 233 | 7.5% |
| 0 | 217 | 7.0% |
| 6 | 212 | 6.9% |
| 5 | 187 | 6.0% |
| 9 | 169 | 5.5% |
| 8 | 151 | 4.9% |
| Other values (25) | 659 |
Fare
Real number (ℝ)
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 182 | 176 |
| Distinct (%) | 40.8% | 39.5% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Infinite | 0 | 0 |
| Infinite (%) | 0.0% | 0.0% |
| Mean | 31.973795 | 31.068908 |
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 0 | 0 |
| Maximum | 512.3292 | 263 |
| Zeros | 6 | 7 |
| Zeros (%) | 1.3% | 1.6% |
| Negative | 0 | 0 |
| Negative (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
Quantile statistics
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 0 | 0 |
| 5-th percentile | 7.125 | 7.22605 |
| Q1 | 7.8958 | 7.925 |
| median | 14.4542 | 14.2 |
| Q3 | 30.64685 | 30.64685 |
| 95-th percentile | 112.67708 | 110.38748 |
| Maximum | 512.3292 | 263 |
| Range | 512.3292 | 263 |
| Interquartile range (IQR) | 22.75105 | 22.72185 |
Descriptive statistics
| Dataset A | Dataset B | |
|---|---|---|
| Standard deviation | 48.505993 | 41.716614 |
| Coefficient of variation (CV) | 1.5170546 | 1.3427126 |
| Kurtosis | 27.743676 | 11.794948 |
| Mean | 31.973795 | 31.068908 |
| Median Absolute Deviation (MAD) | 7.2042 | 6.65 |
| Skewness | 4.3710261 | 3.1220823 |
| Sum | 14260.312 | 13856.733 |
| Variance | 2352.8313 | 1740.2759 |
| Monotonicity | Not monotonic | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 13 | 18 | 4.0% |
| 7.8958 | 18 | 4.0% |
| 8.05 | 17 | 3.8% |
| 10.5 | 16 | 3.6% |
| 7.75 | 15 | 3.4% |
| 26 | 12 | 2.7% |
| 7.2292 | 10 | 2.2% |
| 7.25 | 9 | 2.0% |
| 8.6625 | 8 | 1.8% |
| 7.775 | 8 | 1.8% |
| Other values (172) | 315 |
| Value | Count | Frequency (%) |
| 8.05 | 24 | 5.4% |
| 7.8958 | 22 | 4.9% |
| 26 | 19 | 4.3% |
| 7.75 | 19 | 4.3% |
| 13 | 18 | 4.0% |
| 10.5 | 14 | 3.1% |
| 7.925 | 11 | 2.5% |
| 7.8542 | 9 | 2.0% |
| 7.775 | 8 | 1.8% |
| 8.6625 | 7 | 1.6% |
| Other values (166) | 295 |
| Value | Count | Frequency (%) |
| 0 | 6 | |
| 6.2375 | 1 | 0.2% |
| 6.4375 | 1 | 0.2% |
| 6.45 | 1 | 0.2% |
| 6.4958 | 1 | 0.2% |
| 6.75 | 1 | 0.2% |
| 6.8583 | 1 | 0.2% |
| 6.975 | 2 | 0.4% |
| 7.0458 | 1 | 0.2% |
| 7.05 | 4 |
| Value | Count | Frequency (%) |
| 0 | 7 | |
| 6.4958 | 1 | 0.2% |
| 6.8583 | 1 | 0.2% |
| 6.95 | 1 | 0.2% |
| 6.975 | 1 | 0.2% |
| 7.05 | 4 | |
| 7.125 | 2 | 0.4% |
| 7.225 | 6 | |
| 7.2292 | 5 | |
| 7.25 | 7 |
| Value | Count | Frequency (%) |
| 0 | 7 | |
| 6.4958 | 1 | 0.2% |
| 6.8583 | 1 | 0.2% |
| 6.95 | 1 | 0.2% |
| 6.975 | 1 | 0.2% |
| 7.05 | 4 | |
| 7.125 | 2 | 0.4% |
| 7.225 | 6 | |
| 7.2292 | 5 | |
| 7.25 | 7 |
| Value | Count | Frequency (%) |
| 0 | 6 | |
| 6.2375 | 1 | 0.2% |
| 6.4375 | 1 | 0.2% |
| 6.45 | 1 | 0.2% |
| 6.4958 | 1 | 0.2% |
| 6.75 | 1 | 0.2% |
| 6.8583 | 1 | 0.2% |
| 6.975 | 2 | 0.4% |
| 7.0458 | 1 | 0.2% |
| 7.05 | 4 |
Cabin
['Text', 'Text']
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 82 | 78 |
| Distinct (%) | 85.4% | 80.4% |
| Missing | 350 | 349 |
| Missing (%) | 78.5% | 78.3% |
| Memory size | 7.0 KiB | 7.0 KiB |
Length
| Dataset A | Dataset B | |
|---|---|---|
| Max length | 11 | 15 |
| Median length | 3 | 3 |
| Mean length | 3.5208333 | 3.7113402 |
| Min length | 1 | 1 |
Characters and Unicode
| Dataset A | Dataset B | |
|---|---|---|
| Total characters | 338 | 360 |
| Distinct characters | 18 | 18 |
| Distinct categories | 1 | 1 ? |
| Distinct scripts | 1 | 1 ? |
| Distinct blocks | 1 | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Dataset A | Dataset B | |
|---|---|---|
| Unique | 69 | 61 ? |
| Unique (%) | 71.9% | 62.9% |
Sample
| Dataset A | Dataset B | |
|---|---|---|
| 1st row | D47 | B96 B98 |
| 2nd row | C125 | C22 C26 |
| 3rd row | E34 | B41 |
| 4th row | C2 | G6 |
| 5th row | D26 | C124 |
| Value | Count | Frequency (%) |
| c23 | 3 | 2.7% |
| c27 | 3 | 2.7% |
| f | 3 | 2.7% |
| c25 | 3 | 2.7% |
| d35 | 2 | 1.8% |
| c26 | 2 | 1.8% |
| c22 | 2 | 1.8% |
| b5 | 2 | 1.8% |
| c68 | 2 | 1.8% |
| c2 | 2 | 1.8% |
| Other values (80) | 87 |
| Value | Count | Frequency (%) |
| b96 | 4 | 3.5% |
| b98 | 4 | 3.5% |
| b63 | 2 | 1.7% |
| e101 | 2 | 1.7% |
| c26 | 2 | 1.7% |
| c22 | 2 | 1.7% |
| b22 | 2 | 1.7% |
| d26 | 2 | 1.7% |
| e44 | 2 | 1.7% |
| c2 | 2 | 1.7% |
| Other values (77) | 91 |
Most occurring characters
| Value | Count | Frequency (%) |
| C | 41 | |
| 2 | 39 | |
| 3 | 28 | 8.3% |
| 1 | 26 | 7.7% |
| 4 | 22 | 6.5% |
| B | 22 | 6.5% |
| 6 | 21 | 6.2% |
| 5 | 18 | 5.3% |
| 7 | 16 | 4.7% |
| 8 | 16 | 4.7% |
| Other values (8) | 89 |
| Value | Count | Frequency (%) |
| 2 | 40 | |
| B | 38 | |
| C | 36 | |
| 6 | 31 | 8.6% |
| 1 | 27 | 7.5% |
| 3 | 23 | 6.4% |
| 8 | 21 | 5.8% |
| 9 | 20 | 5.6% |
| E | 19 | 5.3% |
| 7 | 19 | 5.3% |
| Other values (8) | 86 |
Most occurring categories
| Value | Count | Frequency (%) |
| (unknown) | 338 |
| Value | Count | Frequency (%) |
| (unknown) | 360 |
Most frequent character per category
(unknown)
| Value | Count | Frequency (%) |
| C | 41 | |
| 2 | 39 | |
| 3 | 28 | 8.3% |
| 1 | 26 | 7.7% |
| 4 | 22 | 6.5% |
| B | 22 | 6.5% |
| 6 | 21 | 6.2% |
| 5 | 18 | 5.3% |
| 7 | 16 | 4.7% |
| 8 | 16 | 4.7% |
| Other values (8) | 89 |
| Value | Count | Frequency (%) |
| 2 | 40 | |
| B | 38 | |
| C | 36 | |
| 6 | 31 | 8.6% |
| 1 | 27 | 7.5% |
| 3 | 23 | 6.4% |
| 8 | 21 | 5.8% |
| 9 | 20 | 5.6% |
| E | 19 | 5.3% |
| 7 | 19 | 5.3% |
| Other values (8) | 86 |
Most occurring scripts
| Value | Count | Frequency (%) |
| (unknown) | 338 |
| Value | Count | Frequency (%) |
| (unknown) | 360 |
Most frequent character per script
(unknown)
| Value | Count | Frequency (%) |
| C | 41 | |
| 2 | 39 | |
| 3 | 28 | 8.3% |
| 1 | 26 | 7.7% |
| 4 | 22 | 6.5% |
| B | 22 | 6.5% |
| 6 | 21 | 6.2% |
| 5 | 18 | 5.3% |
| 7 | 16 | 4.7% |
| 8 | 16 | 4.7% |
| Other values (8) | 89 |
| Value | Count | Frequency (%) |
| 2 | 40 | |
| B | 38 | |
| C | 36 | |
| 6 | 31 | 8.6% |
| 1 | 27 | 7.5% |
| 3 | 23 | 6.4% |
| 8 | 21 | 5.8% |
| 9 | 20 | 5.6% |
| E | 19 | 5.3% |
| 7 | 19 | 5.3% |
| Other values (8) | 86 |
Most occurring blocks
| Value | Count | Frequency (%) |
| (unknown) | 338 |
| Value | Count | Frequency (%) |
| (unknown) | 360 |
Most frequent character per block
(unknown)
| Value | Count | Frequency (%) |
| C | 41 | |
| 2 | 39 | |
| 3 | 28 | 8.3% |
| 1 | 26 | 7.7% |
| 4 | 22 | 6.5% |
| B | 22 | 6.5% |
| 6 | 21 | 6.2% |
| 5 | 18 | 5.3% |
| 7 | 16 | 4.7% |
| 8 | 16 | 4.7% |
| Other values (8) | 89 |
| Value | Count | Frequency (%) |
| 2 | 40 | |
| B | 38 | |
| C | 36 | |
| 6 | 31 | 8.6% |
| 1 | 27 | 7.5% |
| 3 | 23 | 6.4% |
| 8 | 21 | 5.8% |
| 9 | 20 | 5.6% |
| E | 19 | 5.3% |
| 7 | 19 | 5.3% |
| Other values (8) | 86 |
Embarked
Categorical
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 3 | 3 |
| Distinct (%) | 0.7% | 0.7% |
| Missing | 2 | 1 |
| Missing (%) | 0.4% | 0.2% |
| Memory size | 7.0 KiB | 7.0 KiB |
| S | |
|---|---|
| C | |
| Q |
| S | |
|---|---|
| C | |
| Q |
Length
| Dataset A | Dataset B | |
|---|---|---|
| Max length | 1 | 1 |
| Median length | 1 | 1 |
| Mean length | 1 | 1 |
| Min length | 1 | 1 |
Characters and Unicode
| Dataset A | Dataset B | |
|---|---|---|
| Total characters | 444 | 445 |
| Distinct characters | 3 | 3 |
| Distinct categories | 1 | 1 ? |
| Distinct scripts | 1 | 1 ? |
| Distinct blocks | 1 | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Dataset A | Dataset B | |
|---|---|---|
| Unique | 0 | 0 ? |
| Unique (%) | 0.0% | 0.0% |
Sample
| Dataset A | Dataset B | |
|---|---|---|
| 1st row | S | C |
| 2nd row | S | S |
| 3rd row | S | S |
| 4th row | S | C |
| 5th row | S | S |
Common Values
| Value | Count | Frequency (%) |
| S | 313 | |
| C | 90 | 20.2% |
| Q | 41 | 9.2% |
| (Missing) | 2 | 0.4% |
| Value | Count | Frequency (%) |
| S | 324 | |
| C | 79 | 17.7% |
| Q | 42 | 9.4% |
| (Missing) | 1 | 0.2% |
Length
Histogram of lengths of the category
Common Values (Plot)
Dataset A
Dataset B
| Value | Count | Frequency (%) |
| s | 313 | |
| c | 90 | 20.3% |
| q | 41 | 9.2% |
| Value | Count | Frequency (%) |
| s | 324 | |
| c | 79 | 17.8% |
| q | 42 | 9.4% |
Most occurring characters
| Value | Count | Frequency (%) |
| S | 313 | |
| C | 90 | 20.3% |
| Q | 41 | 9.2% |
| Value | Count | Frequency (%) |
| S | 324 | |
| C | 79 | 17.8% |
| Q | 42 | 9.4% |
Most occurring categories
| Value | Count | Frequency (%) |
| (unknown) | 444 |
| Value | Count | Frequency (%) |
| (unknown) | 445 |
Most frequent character per category
(unknown)
| Value | Count | Frequency (%) |
| S | 313 | |
| C | 90 | 20.3% |
| Q | 41 | 9.2% |
| Value | Count | Frequency (%) |
| S | 324 | |
| C | 79 | 17.8% |
| Q | 42 | 9.4% |
Most occurring scripts
| Value | Count | Frequency (%) |
| (unknown) | 444 |
| Value | Count | Frequency (%) |
| (unknown) | 445 |
Most frequent character per script
(unknown)
| Value | Count | Frequency (%) |
| S | 313 | |
| C | 90 | 20.3% |
| Q | 41 | 9.2% |
| Value | Count | Frequency (%) |
| S | 324 | |
| C | 79 | 17.8% |
| Q | 42 | 9.4% |
Most occurring blocks
| Value | Count | Frequency (%) |
| (unknown) | 444 |
| Value | Count | Frequency (%) |
| (unknown) | 445 |
Most frequent character per block
(unknown)
| Value | Count | Frequency (%) |
| S | 313 | |
| C | 90 | 20.3% |
| Q | 41 | 9.2% |
| Value | Count | Frequency (%) |
| S | 324 | |
| C | 79 | 17.8% |
| Q | 42 | 9.4% |
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
A simple visualization of nullity by column.
Dataset B
A simple visualization of nullity by column.
Dataset A
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
Dataset B
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
Dataset A
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
Dataset B
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
Dataset A
| PassengerId | Survived | Pclass | Name | Sex | Age | SibSp | Parch | Ticket | Fare | Cabin | Embarked | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 190 | 191 | 1 | 2 | Pinsky, Mrs. (Rosa) | female | 32.0 | 0 | 0 | 234604 | 13.0000 | NaN | S |
| 747 | 748 | 1 | 2 | Sinkkonen, Miss. Anna | female | 30.0 | 0 | 0 | 250648 | 13.0000 | NaN | S |
| 136 | 137 | 1 | 1 | Newsom, Miss. Helen Monypeny | female | 19.0 | 0 | 2 | 11752 | 26.2833 | D47 | S |
| 609 | 610 | 1 | 1 | Shutes, Miss. Elizabeth W | female | 40.0 | 0 | 0 | PC 17582 | 153.4625 | C125 | S |
| 646 | 647 | 0 | 3 | Cor, Mr. Liudevit | male | 19.0 | 0 | 0 | 349231 | 7.8958 | NaN | S |
| 319 | 320 | 1 | 1 | Spedden, Mrs. Frederic Oakley (Margaretta Corning Stone) | female | 40.0 | 1 | 1 | 16966 | 134.5000 | E34 | C |
| 336 | 337 | 0 | 1 | Pears, Mr. Thomas Clinton | male | 29.0 | 1 | 0 | 113776 | 66.6000 | C2 | S |
| 197 | 198 | 0 | 3 | Olsen, Mr. Karl Siegwart Andreas | male | 42.0 | 0 | 1 | 4579 | 8.4042 | NaN | S |
| 663 | 664 | 0 | 3 | Coleff, Mr. Peju | male | 36.0 | 0 | 0 | 349210 | 7.4958 | NaN | S |
| 178 | 179 | 0 | 2 | Hale, Mr. Reginald | male | 30.0 | 0 | 0 | 250653 | 13.0000 | NaN | S |
Dataset B
| PassengerId | Survived | Pclass | Name | Sex | Age | SibSp | Parch | Ticket | Fare | Cabin | Embarked | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 693 | 694 | 0 | 3 | Saad, Mr. Khalil | male | 25.0 | 0 | 0 | 2672 | 7.2250 | NaN | C |
| 763 | 764 | 1 | 1 | Carter, Mrs. William Ernest (Lucile Polk) | female | 36.0 | 1 | 2 | 113760 | 120.0000 | B96 B98 | S |
| 297 | 298 | 0 | 1 | Allison, Miss. Helen Loraine | female | 2.0 | 1 | 2 | 113781 | 151.5500 | C22 C26 | S |
| 762 | 763 | 1 | 3 | Barah, Mr. Hanna Assi | male | 20.0 | 0 | 0 | 2663 | 7.2292 | NaN | C |
| 606 | 607 | 0 | 3 | Karaic, Mr. Milan | male | 30.0 | 0 | 0 | 349246 | 7.8958 | NaN | S |
| 400 | 401 | 1 | 3 | Niskanen, Mr. Juha | male | 39.0 | 0 | 0 | STON/O 2. 3101289 | 7.9250 | NaN | S |
| 587 | 588 | 1 | 1 | Frolicher-Stehli, Mr. Maxmillian | male | 60.0 | 1 | 1 | 13567 | 79.2000 | B41 | C |
| 514 | 515 | 0 | 3 | Coleff, Mr. Satio | male | 24.0 | 0 | 0 | 349209 | 7.4958 | NaN | S |
| 105 | 106 | 0 | 3 | Mionoff, Mr. Stoytcho | male | 28.0 | 0 | 0 | 349207 | 7.8958 | NaN | S |
| 29 | 30 | 0 | 3 | Todoroff, Mr. Lalio | male | NaN | 0 | 0 | 349216 | 7.8958 | NaN | S |
Dataset A
| PassengerId | Survived | Pclass | Name | Sex | Age | SibSp | Parch | Ticket | Fare | Cabin | Embarked | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 433 | 434 | 0 | 3 | Kallio, Mr. Nikolai Erland | male | 17.0 | 0 | 0 | STON/O 2. 3101274 | 7.1250 | NaN | S |
| 287 | 288 | 0 | 3 | Naidenoff, Mr. Penko | male | 22.0 | 0 | 0 | 349206 | 7.8958 | NaN | S |
| 577 | 578 | 1 | 1 | Silvey, Mrs. William Baird (Alice Munger) | female | 39.0 | 1 | 0 | 13507 | 55.9000 | E44 | S |
| 105 | 106 | 0 | 3 | Mionoff, Mr. Stoytcho | male | 28.0 | 0 | 0 | 349207 | 7.8958 | NaN | S |
| 602 | 603 | 0 | 1 | Harrington, Mr. Charles H | male | NaN | 0 | 0 | 113796 | 42.4000 | NaN | S |
| 702 | 703 | 0 | 3 | Barbara, Miss. Saiide | female | 18.0 | 0 | 1 | 2691 | 14.4542 | NaN | C |
| 138 | 139 | 0 | 3 | Osen, Mr. Olaf Elon | male | 16.0 | 0 | 0 | 7534 | 9.2167 | NaN | S |
| 464 | 465 | 0 | 3 | Maisner, Mr. Simon | male | NaN | 0 | 0 | A/S 2816 | 8.0500 | NaN | S |
| 6 | 7 | 0 | 1 | McCarthy, Mr. Timothy J | male | 54.0 | 0 | 0 | 17463 | 51.8625 | E46 | S |
| 708 | 709 | 1 | 1 | Cleaver, Miss. Alice | female | 22.0 | 0 | 0 | 113781 | 151.5500 | NaN | S |
Dataset B
| PassengerId | Survived | Pclass | Name | Sex | Age | SibSp | Parch | Ticket | Fare | Cabin | Embarked | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 536 | 537 | 0 | 1 | Butt, Major. Archibald Willingham | male | 45.0 | 0 | 0 | 113050 | 26.5500 | B38 | S |
| 190 | 191 | 1 | 2 | Pinsky, Mrs. (Rosa) | female | 32.0 | 0 | 0 | 234604 | 13.0000 | NaN | S |
| 411 | 412 | 0 | 3 | Hart, Mr. Henry | male | NaN | 0 | 0 | 394140 | 6.8583 | NaN | Q |
| 481 | 482 | 0 | 2 | Frost, Mr. Anthony Wood "Archie" | male | NaN | 0 | 0 | 239854 | 0.0000 | NaN | S |
| 340 | 341 | 1 | 2 | Navratil, Master. Edmond Roger | male | 2.0 | 1 | 1 | 230080 | 26.0000 | F2 | S |
| 61 | 62 | 1 | 1 | Icard, Miss. Amelie | female | 38.0 | 0 | 0 | 113572 | 80.0000 | B28 | NaN |
| 857 | 858 | 1 | 1 | Daly, Mr. Peter Denis | male | 51.0 | 0 | 0 | 113055 | 26.5500 | E17 | S |
| 506 | 507 | 1 | 2 | Quick, Mrs. Frederick Charles (Jane Richards) | female | 33.0 | 0 | 2 | 26360 | 26.0000 | NaN | S |
| 708 | 709 | 1 | 1 | Cleaver, Miss. Alice | female | 22.0 | 0 | 0 | 113781 | 151.5500 | NaN | S |
| 187 | 188 | 1 | 1 | Romaine, Mr. Charles Hallace ("Mr C Rolmane") | male | 45.0 | 0 | 0 | 111428 | 26.5500 | NaN | S |
Dataset A
| PassengerId | Survived | Pclass | Name | Sex | Age | SibSp | Parch | Ticket | Fare | Cabin | Embarked | # duplicates | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dataset does not contain duplicate rows. | |||||||||||||
Dataset B
| PassengerId | Survived | Pclass | Name | Sex | Age | SibSp | Parch | Ticket | Fare | Cabin | Embarked | # duplicates | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dataset does not contain duplicate rows. | |||||||||||||